We are seeking a skilled and forward-looking ML Engineer with experience in Large Language Models (LLMs), generative AI, and agentic architectures to join our growing R&D and Applied AI team. This role is critical in helping Oversight deliver the next generation of agentic AI systems for enterprise spend management and risk controls.
Required
Bachelor’s or Master’s degree in Computer Science, Data Science, Machine Learning, or related field.
5+ years of experience building and deploying ML systems.
Proficiency in Python and libraries such as PyTorch, TensorFlow, Scikit-Learn, Hugging Face Transformers.
Hands-on experience with LLMs/SLMs (fine-tuning, prompt design, inference optimization).
Demonstrated experience with at least two of the following ecosystems: o OpenAI GPT models (chat, assistants, fine-tuning). o Anthropic Claude (safety-first AI for reasoning and summarization). o Google Gemini (multimodal reasoning, enterprise-scale APIs). o Meta LLaMA (open-source, fine-tuned models).
Familiarity with vector databases, embeddings, and RAG pipelines.
Ability to work with structured and unstructured data at scale.
Knowledge of SQL and distributed data frameworks (Spark, Ray).
Strong understanding of ML lifecycle: data prep, training, evaluation, deployment, monitoring.
Preferred Qualifications
Experience with agentic frameworks (LangChain, LangGraph, MCP, AutoGen).
Knowledge of AI safety, guardrails, and explainability techniques.
Hands-on experience deploying ML/LLM solutions in cloud environments (AWS, GCP, Azure).
Experience with CI/CD for ML (MLOps), monitoring, and observability.
Familiarity with anomaly detection, fraud/risk modeling, or behavioral analytics.
Contributions to open-source AI/ML projects or publications in applied ML research
If you are interested, please send your resume in English to: [email protected], including your salary expectation.